Wewei Zhang, Hongyong Zhao, Chunlin Sha, Jinde Cao
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Quantized Projective Synchronization of Delayed Fractional Order Uncertain Quaternion-Valued Neural Networks Via Direct Method
This paper treats the projective synchronization (PS) in finite time for a class of delayed fractional order uncertain quaternion-valued neural networks (DFOUQVNNs) based on event triggered quantized control (ETQC). In addition, to consider more general models, uncertainty and time delay terms are introduced into the FOQVNNs. Different from using decomposition method, the considered model is treated as a single entity. By designing a suitable Lyapunov function and applying inequality skills, sufficient criteria are derived to ensure PS in finite time of DFOUQVNNs. Furthermore, the setting time is estimated and the Zeno behavior of the system is excluded under the proposed scheme. Finally, the effectiveness of the theoretical results is validated by using a numerical example.
期刊介绍：
Mathematical Methods in the Applied Sciences publishes papers dealing with new mathematical methods for the consideration of linear and non-linear, direct and inverse problems for physical relevant processes over time- and space- varying media under certain initial, boundary, transition conditions etc. Papers dealing with biomathematical content, population dynamics and network problems are most welcome.
Mathematical Methods in the Applied Sciences is an interdisciplinary journal: therefore, all manuscripts must be written to be accessible to a broad scientific but mathematically advanced audience. All papers must contain carefully written introduction and conclusion sections, which should include a clear exposition of the underlying scientific problem, a summary of the mathematical results and the tools used in deriving the results. Furthermore, the scientific importance of the manuscript and its conclusions should be made clear. Papers dealing with numerical processes or which contain only the application of well established methods will not be accepted.
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